ANALISIS KEBERHASILAN APLIKASI E-FITNESS DENGAN MOTIVASI SEBAGAI VARIABEL MEDIASI: PENDEKATAN MODEL DELONE & MCLEAN

Arjun Naja; Anggyi Trisnawan Putra

doi:10.36549/ijis.v11i2.494

ANALISIS KEBERHASILAN APLIKASI E-FITNESS DENGAN MOTIVASI SEBAGAI VARIABEL MEDIASI: PENDEKATAN MODEL DELONE & MCLEAN

Arjun Naja, Anggyi Trisnawan Putra

Sari

Tingginya angka pengguna aplikasi e-fitness di Indonesia tidak serta-merta mencerminkan keberhasilan sistem. Rendahnya konsistensi penggunaan menunjukkan bahwa faktor psikologis dan lingkungan turut menentukan keberhasilan aplikasi. Penelitian mengenai keberhasilan aplikasi kesehatan digital berbasis model DeLone & McLean belum mengkaji motivasi sebagai variabel mediasi antara faktor lingkungan dan keberhasilan aplikasi e-fitness. Penelitian ini bertujuan menganalisis pengaruh faktor lingkungan terhadap keberhasilan aplikasi e-fitness menggunakan model DeLone & McLean dengan motivasi sebagai variabel mediasi. Penelitian menggunakan pendekatan kuantitatif melalui survei eksplanatori dan analisis Structural Equation Modeling berbasis Partial Least Squares (SEM-PLS). Data dikumpulkan dari 151 pengguna aplikasi e-fitness di Kabupaten Kendal melalui kuesioner daring. Hasil menunjukkan overall quality dan faktor lingkungan berpengaruh positif dan signifikan terhadap motivasi; motivasi berpengaruh positif terhadap penggunaan; penggunaan berpengaruh terhadap kepuasan; dan kepuasan berpengaruh terhadap manfaat bersih. Motivasi terbukti memediasi penuh pengaruh faktor lingkungan terhadap penggunaan aplikasi. Temuan ini memperkaya kajian keberhasilan sistem informasi, khususnya aplikasi kebugaran digital.

Kata Kunci: E-fitness, DeLone & McLean, Faktor Lingkungan, Motivasi, SEM-PLS

Teks Lengkap:

PDF (Indonesia)

Referensi

N. K. Lee and J. S. Kim, “Status and trends of the digital healthcare industry,” Healthc. Inform. Res., vol. 30, no. 3, pp. 172–183, 2024, DOI: 10.4258/hir.2024.30.3.172.

A. B. M. N. Hasan, A. Bin Sharif, and I. Jahan, “Perceived barriers to maintain physical activity and its association to mental health status of Bangladeshi adults: a quantile regression approach,” Sci. Rep., vol. 13, no. 1, p. 8993, Jul. 2023, DOI: 10.1038/s41598-023-36299-7.

A. L. Karunanayake, C. D. Senaratne, and A. Stathi, “A descriptive cross sectional study comparing barriers and determinants of physical activity of Sri Lankan middle aged and older adults,” PLoS One, vol. 15, no. 5, p. e0232956, Jul. 2020, DOI: 10.1371/journal.pone.0232956.

M. N. Woessner, A. Tacey, A. Levinger-Limor, A. G. Parker, P. Levinger, and I. Levinger, “The Evolution of Technology and Physical Inactivity: The Good, the Bad, and the Way Forward,” Front. Public Heal., vol. 9, p. 655491, 2021, DOI: 10.3389/fpubh.2021.655491.

Kementerian Pemuda dan Olahraga Republik Indonesia, “Laporan Nasional Sport Development Index Tahun 2023,” Jakarta, 2024. [Online]. Available: https://img-deputi2.kemenpora.go.id/files/document_file/2024/06/25/34/1143laporan-nasional-sport-development-index-tahun-2023.pdf

K. D. P. Novianti, “Analisis Evaluasi E-learning Menggunakan Integrasi Model D&M dan UTAUT,” Techno.Com, vol. 18, no. 2, pp. 122–133, 2019, DOI: 10.33633/tc.v18i2.2217.

W. H. DeLone and E. R. McLean, “The DeLone and McLean model of information systems success: A ten-year update,” J. Manag. Inf. Syst., vol. 19, no. 4, pp. 9–30, 2003, DOI: 10.1080/07421222.2003.11045748.

A. Aldholay, O. Isaac, Z. Abdullah, R. Abdulsalam, and A. H. Al-Shibami, “An extension of Delone and McLean IS success model with self-efficacy: Online learning usage in Yemen,” Int. J. Inf. Learn. Technol., vol. 35, no. 4, pp. 285–304, Jan. 2018, DOI: 10.1108/IJILT-11-2017-0116.

C. Wang and H. Qi, “Influencing Factors of Acceptance and Use Behavior of Mobile Health Application Users: Systematic Review,” Healthcare, vol. 9, no. 3, p. 357, 2021, DOI: 10.3390/healthcare9030357.

A. Bandura, Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall, 1986.

R. Ryan and E. Deci, “Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being.,” Am. Psychol., vol. 55, no. 1, pp. 68–78, Jan. 2000, DOI: 10.1037/0003-066X.55.1.68.

Y. Zhang, Hasibagen, and C. Zhang, “The influence of social support on the physical exercise behavior of college students: The mediating role of self-efficacy,” Front. Psychol., vol. 13, p. 1037518, Jul. 2022, DOI: 10.3389/fpsyg.2022.1037518.

A. Herian, A. Faroqi, and T. L. M. Suryanto, “Evaluasi Penerimaan Pengguna Aplikasi Kebugaran Smartphone Menggunakan UTAUT2,” Inf. (Jurnal Inform. dan Sist. Informasi), vol. 17, no. 1, pp. 100–116, 2025.

U. Merdekawati, D. M. K. Nugraheni, and O. D. Nurhayati, “Analisis Penerimaan dan Kesuksesan Aplikasi M-health pada Lansia menggunakan Model UTAUT dan Delone & McLean,” J. Sist. Inf. Bisnis, vol. 14, no. 3, pp. 267–276, 2024, DOI: 10.21456/vol14iss3pp267-276.

D. E. Conroy, C. Yang, and J. P. Maher, “Behavior Change Techniques in Top-Ranked Mobile Apps for Physical Activity,” Am. J. Prev. Med., vol. 46, no. 6, pp. 649–652, 2014, doi: 10.1016/j.amepre.2014.01.010.

J. Mollee, A. Middelweerd, R. Kurvers, and M. Klein, “What technological features are used in smartphone apps that promote physical activity? A review and content analysis,” Pers. Ubiquitous Comput., vol. 21, pp. 633–643, 2017, DOI: 10.1007/s00779-017-1023-3.

T. Wang et al., “The Association Among Social Support, Self-Efficacy, Use of Mobile Apps, and Physical Activity: Structural Equation Models With Mediating Effects.,” JMIR mHealth uHealth, vol. 7, no. 9, p. e12606, Sep. 2019, DOI: 10.2196/12606.

F. N. Rusmitaningsih, H. Subarjah, Y. Yustiana, and D. R. Saputra, “Enhancing students’ engagement and motivation in physical education: the role of fitness tracker apps,” Edu Sport. Indones. J. Phys. Educ., vol. 5, no. 3, pp. 274–288, 2024, DOI: 10.25299/esijope.2024.vol5(3).17215.

J. Y. Y. Ng et al., “Self-Determination Theory Applied to Health Contexts: A Meta-Analysis.,” Perspect. Psychol. Sci. a J. Assoc. Psychol. Sci., vol. 7, no. 4, pp. 325–340, Jul. 2012, DOI: 10.1177/1745691612447309.

X. Zhang and X. Xu, “Continuous use of fitness apps and shaping factors among college students: A mixed-method investigation,” Int. J. Nurs. Sci., vol. 7, pp. S80–S87, 2020, DOI: 10.1016/j.ijnss.2020.07.009.

J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, “When to use and how to report the results of PLS-SEM,” Eur. Bus. Rev., vol. 31, no. 1, pp. 2–24, Apr. 2019, DOI: 10.1108/EBR-11-2018-0203.

J. Hair, C. L. Hollingsworth, A. B. Randolph, and A. Y. L. Chong, “An updated and expanded assessment of PLS-SEM in information systems research,” Ind. Manag. Data Syst., vol. 117, no. 3, pp. 442–458, Feb. 2017, DOI: 10.1108/IMDS-04-2016-0130.

J. Henseler et al., “Common beliefs and reality about pls: comments on rönkkö and evermann(2013),” Organ. Res. Methods, vol. 17, no. 2, pp. 182–209, Feb. 2014, DOI: 10.1177/1094428114526928.

M. Nam et al., “Effects of content characteristics and improvement in user satisfaction on the reuse of home fitness application,” Sustainability, vol. 15, no. 10, p. 8371, Jul. 2023, DOI: 10.3390/su15108371.

Y. Zhao, Q. Ni, and R. Zhou, “What factors influence the mobile health service adoption? A meta-analysis and the moderating role of age,” Int. J. Inf. Manage., vol. 43, pp. 342–350, Jul. 2018, DOI: 10.1016/j.ijinfomgt.2017.08.006.

DOI: https://doi.org/10.36549/ijis.v11i2.494